Energy efficiency is a critical issue for battery-operated unmanned ground sensor (UGS) devices. Specifically, in a UGS network where each node is responsible for forwarding data packets from neighboring nodes to an upstream node, care has to be taken not only to reduce the overall energy consumption of all associated nodes, but also to balance battery levels (power availability) of each of the nodes. Unbalanced energy usage will result in faster node failures in overloaded nodes, which in turn may lead to network partitioning and reduced network lifetime.
Generally, existing energy-aware algorithms assume a static network. Additionally, a node must wait until all possible paths have been evaluated based on given energy-aware metrics before selecting the best routing path. Conventional methods of finding a routing path would require a relatively long period of time for collection, and continuous updating thereafter, of the global topology knowledge.
Many sensor routing protocols have been proposed based on modifications to existing ad hoc network protocols. Generally, sensor routing protocols can be classified into three categories: one-hop, flat and cluster-based hierarchical protocols. In one-hop protocols, a sensor node sends data directly to the ultimate data collection device, called a sink. This is not only expensive in terms of energy consumption, but it is also impractical for many applications because sensor nodes have limited transmission range. Flat protocols involve a source node transmitting data to the sink by forwarding its data to one of its neighbors which is closer to the sink. Thus, data travels from the source to sink by “hopping” from one node to another until it arrives at the destination. Some flat protocols use optimization techniques to enhance the energy efficiency of the devices in the network. Although these optimization techniques improve the performance of this model, it is still a flat model that exhibits high latency. A cluster-based routing protocol groups sensor nodes to efficiently relay the sensed data to the sink. Each group of sensors has a cluster head or gateway. Cluster heads may be specialized nodes that are less energy-constrained. A cluster-head performs some aggregation function on data it receives and sends it to the sink as a representative sample of its cluster. Cluster formation is a design approach that minimizes energy consumption and latency. The factors affecting cluster formation, cluster-head selection and data aggregation and fusion among clusters are critical issues.
There are numerous drawbacks encountered when applying existing routing protocols to UGS networks. First, existing routing protocols can not handle time-critical applications because time synchronization was not considered in the design of existing routing protocols. Second, in order to maintain the routing table up to date, nodes have to periodically transmit beacon messages to their neighbors to determine their status. This generates undesirable overhead which, in turn, drains battery power of a node device. Third, existing protocol techniques are geared to handle very large numbers of sensor nodes (typically >10,000) that are scattered all over an area. Consequently, these techniques are not optimal for networks having, for example, as few as 20 nodes.
There are several features desired in a routing protocol for energy conservation in a UGS network. First, it is important that the routing protocol accommodate dynamic clustering architectures to prevent cluster heads from depleting their power, and hence extending the lifetime of the network. Second, efficient selection of a path is desirable to facilitate load balancing and, thus, be more tolerant to node failures. This can be accomplished with routing protocols that are capable of maintaining multiple low overhead routing paths. Third, the protocol should minimize over-the-air (OTA) transmissions by nodes. Fewer OTA transmission (i.e., beacon, topology updates, etc.) contribute to preserving battery life of a node device. Fourth, thresholds should be set for sensor nodes to transfer data to solve “hot spot” problems and saving energy by limiting unnecessary transmissions. Finally, thresholds should be provided for sensor nodes to relay data. That is, the capability to specify thresholds for energy and time delay when relaying data between nodes may better regulate transmissions and thereby extend the lifetime of a node device.